Since the financial crisis, the issue of the 'one percent' has become the centre of intense public debate, unavoidable even for members of the elite themselves. Moreover, inquiring into elites has taken centre-stage once again in both journalistic investigations and academic research. New Directions in Elite Studies attempts to move the social scientific study of elites beyond economic analysis, which has greatly improved our knowledge of inequality, but is restricted to income and wealth. In contrast, this book mobilizes a broad scope of research methods to uncover the social composition of the power elite - the 'field of power'. It reconstructs processes through which people gain access to positions in this particular social space, examines the various forms of capital they mobilize in the process - economic, but also cultural and social capital - and probes changes over time and variations across national contexts. Bringing together the most advanced research into elites by a European and multidisciplinary group of scholars, this book presents an agenda for the future study of elites. It will appeal to all those interested in the study of elites, inequality, class, power, and gender inequality.

The Handbook of U.S. Labor Statistics is recognized as an authoritative resource on the U.S. labor force. It continues and enhances the Bureau of Labor Statistics's (BLS) discontinued publication, Labor Statistics. It allows the user to understand recent developments as well as to compare today's economy with past history. This edition includes new tables on occupational safety and health and income in the United States. The Handbook is a comprehensive reference providing an abundance of data on a variety of topics including: *Employment and unemployment; *Earnings; *Prices; *Productivity; *Consumer expenditures; *Occupational safety and health; *Union membership; *Working poor *And much more! Features of the publication In addition to over 215 tables that present practical data, the Handbook provides: *Introductory material for each chapter that contains highlights of salient data and figures that call attention to noteworthy trends in the data *Notes and definitions, which contain concise descriptions of the data sources, concepts, definitions, and methodology from which the data are derived *References to more comprehensive reports which provide additional data and more extensive descriptions of estimation methods, sampling, and reliability measures

An understanding of the behaviour of financial assets and the evolution of economies has never been as important as today. This book looks at these complex systems from the perspective of the physicist. So called 'econophysics' and its application to finance has made great strides in recent years. Less emphasis has been placed on the broader subject of macroeconomics and many economics students are still taught traditional neo-classical economics. The reader is given a general primer in statistical physics, probability theory, and use of correlation functions. Much of the mathematics that is developed is frequently no longer included in undergraduate physics courses. The statistical physics of Boltzmann and Gibbs is one of the oldest disciplines within physics and it can be argued that it was first applied to ensembles of molecules as opposed to being applied to social agents only by way of historical accident. The authors argue by analogy that the theory can be applied directly to economic systems comprising assemblies of interacting agents. The necessary tools and mathematics are developed in a clear and concise manner. The body of work, now termed econophysics, is then developed. The authors show where traditional methods break down and show how the probability distributions and correlation functions can be properly understood using high frequency data. Recent work by the physics community on risk and market crashes are discussed together with new work on betting markets as well as studies of speculative peaks that occur in housing markets. The second half of the book continues the empirical approach showing how by analogy with thermodynamics, a self-consistent attack can be made on macroeconomics. This leads naturally to economic production functions being equated to entropy functions - a new concept for economists. Issues relating to non-equilibrium naturally arise during the development and application of this approach to economics. These are discussed in the context of superstatistics and adiabatic processes. As a result it does seem ultimately possible to reconcile the approach with non-equilibrium systems, and the ideas are applied to study income and wealth distributions, which with their power law distribution functions have puzzled many researchers ever since Pareto discovered them over 100 years ago. This book takes a pedagogical approach to these topics and is aimed at final year undergraduate and beginning gradaute or post-graduate students in physics, economics, and business. However, the experienced researcher and quant should also find much of interest.

Suitable for statisticians, mathematicians, actuaries, and students interested in the problems of insurance and analysis of lifetimes, Statistical Methods with Applications to Demography and Life Insurance presents contemporary statistical techniques for analyzing life distributions and life insurance problems. It not only contains traditional material but also incorporates new problems and techniques not discussed in existing actuarial literature. The book mainly focuses on the analysis of an individual life and describes statistical methods based on empirical and related processes. Coverage ranges from analyzing the tails of distributions of lifetimes to modeling population dynamics with migrations. To help readers understand the technical points, the text covers topics such as the Stieltjes, Wiener, and Ito integrals. It also introduces other themes of interest in demography, including mixtures of distributions, analysis of longevity and extreme value theory, and the age structure of a population. In addition, the author discusses net premiums for various insurance policies. Mathematical statements are carefully and clearly formulated and proved while avoiding excessive technicalities as much as possible. The book illustrates how these statements help solve numerous statistical problems. It also includes more than 70 exercises.

This book aims to bring together studies using different data types (panel data, cross-sectional data and time series data) and different methods (for example, panel regression, nonlinear time series, chaos approach, deep learning, machine learning techniques among others) and to create a source for those interested in these topics and methods by addressing some selected applied econometrics topics which have been developed in recent years. It creates a common meeting ground for scientists who give econometrics education in Turkey to study, and contribute to the delivery of the authors' knowledge to the people who take interest. This book can also be useful for "Applied Economics and Econometrics" courses in postgraduate education as a material source

"It's the economy, stupid," as Democratic strategist James Carville would say. After many years of study, Ray C. Fair has found that the state of the economy has a dominant influence on national elections. Just in time for the 2012 presidential election, this new edition of his classic text, "Predicting Presidential Elections and Other Things," provides us with a look into the likely future of our nation's political landscape--but Fair doesn't stop there.
Fair puts other national issues under the microscope as well--including congressional elections, Federal Reserve behavior, and inflation. In addition he covers topics well beyond today's headlines, as the book takes on questions of more direct, personal interest such as wine quality, predicting football games, and aging effects in baseball. Which of your friends is most likely to have an extramarital affair? How important is class attendance for academic performance in college? How fast can you expect to run a race or perform some physical task at age 55, given your time at age 30? Read "Predicting Presidential Elections and Other Things" and find out
As Fair works his way through an incredibly broad range of questions and topics, he teaches and delights. The discussion that underlies each chapter topic moves from formulating theories about real world phenomena to lessons on how to analyze data, test theories, and make predictions. At the end of this book, readers will walk away with more than mere predictions. They will have learned a new approach to thinking about many age-old concerns in public and private life, and will have a myriad of fun facts to share.

Quants, physicists working on Wall Street as quantitative analysts, have been widely blamed for triggering financial crises with their complex mathematical models. Their formulas were meant to allow Wall Street to prosper without risk. But in this penetrating insider's look at the recent economic collapse, Emanuel Derman--former head quant at Goldman Sachs--explains the collision between mathematical modeling and economics and what makes financial models so dangerous. Though such models imitate the style of physics and employ the language of mathematics, theories in physics aim for a description of reality--but in finance, models can shoot only for a very limited approximation of reality. Derman uses his firsthand experience in financial theory and practice to explain the complicated tangles that have paralyzed the economy. "Models.Behaving.Badly. "exposes Wall Street's love affair with models, and shows us why nobody will ever be able to write a model that can encapsulate human behavior.

The book aims at perfecting the national governance system and improving national governance ability. It evaluates the balance sheets of the state and residents, non-financial corporations, financial institutions and the central bank, the central government, local government and external sectors - the goal being to provide a systematic analysis of the characteristics and trajectory of China's economic expansion and structural adjustment, as well as objective assessments of short and long-term economic operations, debt risks and financial risks with regard to the institutional and structural characteristics of economic development in market-oriented reform. It puts forward a preliminary analysis of China's national and sectoral balance sheets on the basis of scientific estimates of various kinds of data, analyzes from a new perspective the major issues that are currently troubling China - development sustainability, government transformation, local government debt, welfare reform, and the financial opening-up and stability - and explores corresponding policies, measures, and institutional arrangements.

How we pay is so fundamental that it underpins everything – from trade to taxation, stocks and savings to salaries, pensions and pocket money. Rich or poor, criminal, communist or capitalist, we all rely on the same payments system, day in, day out. It sits between us and not just economic meltdown, but a total breakdown in law and order. Why then do we know so little about how that system really works?

Leibbrandt and de Terán shine a light on the hidden workings of the humble payment – and reveal both how our payment habits are determined by history as well as where we might go next. From national customs to warring nation states, geopolitics will shape the future of payments every bit as much as technology.

Challenging our understanding about where financial power really lies, The Pay Off shows us that the most important thing about money is the way we move it.

Over the last decade, dynamical systems theory and related nonlinear methods have had a major impact on the analysis of time series data from complex systems. Recent developments in mathematical methods of state-space reconstruction, time-delay embedding, and surrogate data analysis, coupled with readily accessible and powerful computational facilities used in gathering and processing massive quantities of high-frequency data, have provided theorists and practitioners unparalleled opportunities for exploratory data analysis, modelling, forecasting, and control.
Until now, research exploring the application of nonlinear dynamics and associated algorithms to the study of economies and markets as complex systems is sparse and fragmentary at best. Modelling and Forecasting Financial Data brings together a coherent and accessible set of chapters on recent research results on this topic. To make such methods readily useful in practice, the contributors to this volume have agreed to make available to readers upon request all computer programs used to implement the methods discussed in their respective chapters.
Modelling and Forecasting Financial Data is a valuable resource for researchers and graduate students studying complex systems in finance, biology, and physics, as well as those applying such methods to nonlinear time series analysis and signal processing.

Pathwise estimation and inference for diffusion market models discusses contemporary techniques for inferring, from options and bond prices, the market participants' aggregate view on important financial parameters such as implied volatility, discount rate, future interest rate, and their uncertainty thereof. The focus is on the pathwise inference methods that are applicable to a sole path of the observed prices and do not require the observation of an ensemble of such paths. This book is pitched at the level of senior undergraduate students undertaking research at honors year, and postgraduate candidates undertaking Master's or PhD degree by research. From a research perspective, this book reaches out to academic researchers from backgrounds as diverse as mathematics and probability, econometrics and statistics, and computational mathematics and optimization whose interest lie in analysis and modelling of financial market data from a multi-disciplinary approach. Additionally, this book is also aimed at financial market practitioners participating in capital market facing businesses who seek to keep abreast with and draw inspiration from novel approaches in market data analysis. The first two chapters of the book contains introductory material on stochastic analysis and the classical diffusion stock market models. The remaining chapters discuss more special stock and bond market models and special methods of pathwise inference for market parameter for different models. The final chapter describes applications of numerical methods of inference of bond market parameters to forecasting of short rate. Nikolai Dokuchaev is an associate professor in Mathematics and Statistics at Curtin University. His research interests include mathematical and statistical finance, stochastic analysis, PDEs, control, and signal processing. Lin Yee Hin is a practitioner in the capital market facing industry. His research interests include econometrics, non-parametric regression, and scientific computing.

Originally published in 1978. This book is designed to enable students on main courses in economics to comprehend literature which employs econometric techniques as a method of analysis, to use econometric techniques themselves to test hypotheses about economic relationships and to understand some of the difficulties involved in interpreting results. While the book is mainly aimed at second-year undergraduates undertaking courses in applied economics, its scope is sufficiently wide to take in students at postgraduate level who have no background in econometrics - it integrates fully the mathematical and statistical techniques used in econometrics with micro- and macroeconomic case studies.

The papers collected in the two volumes Nonlinear Models focus on the asymptotic theory of parameter estimators of nonlinear single equation models and systems of nonlinear models, in particular weak and strong consistency, asymptotic normality, and parameter inference, for cross-sections as well as for time series. A selection of papers on testing for, and estimation and inference under, model misspecification is also included. The models under review are parametric, hence their functional form is assured to be known up to a vector of unknown parameters, and the functional form involved is nonlinear in at least one of the parameters.The selection of earlier articles on nonlinear parametric models is extensive and, although they are not all equally influential, each has played a significant part in the development of the field. The more recent articles have been selected on the basis of their potential importance for the further development of this sphere of study.

The three volumes of the "Collected Scientific Works of David Cass" are ordered chronologically, which happens to coincide with the development of the three major advances in Cass' research agenda, the development of the neoclassical growth model, the discovery of sunspot equilibria, and the analysis of models of market incompleteness. This volume consists of Cass' early work from his time in graduate school at Stanford University, studying under Hirofumi Uzawa, and as an assistant professor at Yale's Cowles Commission, and his tenure at Carnegie Mellon University's Graduate School of Industrial Administration. The work in this volume focuses primarily on Cass' contributions to what is now known as the Ramsey-Cass-Kooopmans neoclassical growth model, and the development of what is now known as the Cass criterion for determining whether intertemporal allocations are efficient. This period also includes Cass' early work on overlapping generation's models, asset pricing models, and methodological contributions in dynamic systems applications in economics.

The three volumes of the "The Collected Scientific Works of David Cass" are ordered chronologically, which happens to coincide with the development of the three major advances in Cass' research agenda, the development of the neoclassical growth model, the discovery of sunspot equilibria, and the analysis of models of market incompleteness. This volume consists of the work Cass completed after leaving Carnegie Mellon for the University of Pennsylvania's Economics Department (where he remained for the rest of his career). The work during this period encompasses his well-known collaboration with Karl Shell and Yves Balasko on overlapping generations models, and his development with Karl of the notion of 'sunspot equilibria' - rational expectations equilibria which are essentially self-fulfilling prophecies. This period also saw the beginnings of Cass' pioneering research into the theory of incomplete markets, which grew naturally form his early interest in models of asset pricing, and includes the paper which developed what is now known as the Cass trick for analyzing incomplete markets models.

The three volumes of the "Collected Scientific Works of David Cass" are ordered chronologically, which happens to coincide with the development of the three major advances in Cass' research agenda, the development of the neoclassical growth model, the discovery of sunspot equilibria, and the analysis of models of market incompleteness. This volume covers the period from the middle 1980's through the end of Cass' life in 2008. Cass' research during this period included definitive papers showing that competitive equilibrium is generically indeterminate when markets are incomplete, and on the relationship between market incompleteness and the existence of sunspot equilibrium. This period also saw the follow-on papers addressing the issue of how financial innovation affects economic welfare, showing in particular that innovation can lead to welfare losses as well as gains, depending on the nature of the innovation.

This book provides an up-to-date series of advanced chapters on applied financial econometric techniques pertaining the various fields of commodities finance, mathematics & stochastics, international macroeconomics and financial econometrics. Financial Mathematics, Volatility and Covariance Modelling: Volume 2 provides a key repository on the current state of knowledge, the latest debates and recent literature on financial mathematics, volatility and covariance modelling. The first section is devoted to mathematical finance, stochastic modelling and control optimization. Chapters explore the recent financial crisis, the increase of uncertainty and volatility, and propose an alternative approach to deal with these issues. The second section covers financial volatility and covariance modelling and explores proposals for dealing with recent developments in financial econometrics This book will be useful to students and researchers in applied econometrics; academics and students seeking convenient access to an unfamiliar area. It will also be of great interest established researchers seeking a single repository on the current state of knowledge, current debates and relevant literature.

Across the globe every nation wrestles with how it will pay for, provide, regulate and administer its healthcare system. Health economics is the field of economics that deals with every one of those issues and the difficult issue of allocating resources where the allocation can literally mean life or death, alleviating suffering or not. A key issue that is always mentioned, but little acted on, is the role that preventive measures play in the battle against disease and using limited healthcare resources more efficaciously. This book brings together leading researchers in the healthcare economics field presenting new research on some of these key issues such as the impact of obesity on health, children's' healthcare policies, education and health; and many more.

Within the subprime crisis (2007) and the recent global financial crisis of 2008-2009, we have observed significant decline, corrections and structural changes in most US and European financial markets. Furthermore, it seems that this crisis has been rapidly transmitted toward the most developed and emerging countries and has strongly affected the whole economy. This volume aims to present recent researches in linear and nonlinear modelling of economic and financial time-series. The several discussions of empirical results of its chapters clearly help to improve the understanding of the financial mechanisms inherent to this crisis. They also yield an important overview on the sources of the financial crisis and its main economic and financial consequences. The book provides the audience a comprehensive understanding of financial and economic dynamics in various aspects using modern financial econometric methods. It addresses the empirical techniques needed by economic agents to analyze the dynamics of these markets and illustrates how they can be applied to the actual data. It also presents and discusses new research findings and their implications.

This book explores the possibility of using social media data for detecting socio-economic recovery activities. In the last decade, there have been intensive research activities focusing on social media during and after disasters. This approach, which views people's communication on social media as a sensor for real-time situations, has been widely adopted as the "people as sensor" approach. Furthermore, to improve recovery efforts after large-scale disasters, detecting communities' real-time recovery situations is essential, since conventional socio-economic recovery indicators, such as governmental statistics, are not published in real time. Thanks to its timeliness, using social media data can fill the gap. Motivated by this possibility, this book especially focuses on the relationships between people's communication on Twitter and Facebook pages, and socio-economic recovery activities as reflected in the used-car market data and the housing market data in the case of two major disasters: the Great East Japan Earthquake and Tsunami of 2011 and Hurricane Sandy in 2012. The book pursues an interdisciplinary approach, combining e.g. disaster recovery studies, crisis informatics, and economics. In terms of its contributions, firstly, the book sheds light on the "people as sensors" approach for detecting socio-economic recovery activities, which has not been thoroughly studied to date but has the potential to improve situation awareness during the recovery phase. Secondly, the book proposes new socio-economic recovery indicators: used-car market data and housing market data. Thirdly, in the context of using social media during the recovery phase, the results demonstrate the importance of distinguishing between social media data posted both by people who are at or near disaster-stricken areas and by those who are farther away.

This volume is a collection of methodological developments and applications of simulation-based methods that were presented at a workshop at Louisiana State University in November, 2009. The first two papers are extensions of the GHK simulator: one reconsiders the computation of the probabilities in a discrete choice model while another example uses an adaptive version of sparse-grids integration (SGI) instead of simulation. Two studies are focused specifically on the methodology: the first compares the performance of the maximum-simulated likelihood (MSL) approach with a proposed composite marginal likelihood (CML) approach in multivariate ordered-response situations, while the second examines methods of testing for the presence of heterogeneity in the heterogeneity model. Further topics examined include: education savings accounts, parent contributions and education attainment; estimating the effect of exchange rate flexibility on financial account openness; estimating a fractional response model with a count endogenous regressor; and modelling and forecasting volatility in a bayesian approach.

This book describes a system of mathematical models and methods that can be used to analyze real economic and managerial decisions and to improve their effectiveness. Application areas include: management of development and operation budgets, assessment and management of economic systems using an energy entropy approach, equation of exchange rates and forecasting foreign exchange operations, evaluation of innovative projects, monitoring of governmental programs, risk management of investment processes, decisions on the allocation of resources, and identification of competitive industrial clusters. The proposed methods and models were tested on the example of Kazakhstan's economy, but the generated solutions will be useful for applications at other levels and in other countries. Regarding your book "Mathematical Methods and Models in Economics", I am impressed because now it is time when "econometrics" is becoming more appreciated by economists and by schools that are the hosts or employers of modern economists. ... Your presented results really impressed me. John F. Nash, Jr., Princeton University, Nobel Memorial Prize in Economic Sciences The book is within my scope of interest because of its novelty and practicality. First, there is a need for realistic modeling of complex systems, both natural and artificial that conclude computer and economic systems. There has been an ongoing effort in developing models dealing with complexity and incomplete knowledge. Consequently, it is clear to recognize the contribution of Mutanov to encapsulate economic modeling with emphasis on budgeting and innovation. Secondly, the method proposed by Mutanov has been verified by applying to the case of the Republic of Kazakhstan, with her vibrant emerging economy. Thirdly, Chapter 5 of the book is of particular interest for the computer technology community because it deals with innovation. In summary, the book of Mutanov should become one of the outstanding recognized pragmatic guides for dealing with innovative systems. Andrzej Rucinski, University of New Hampshire This book is unique in its theoretical findings and practical applicability. The book is an illuminating study based on an applied mathematical model which uses methods such as linear programming and input-output analysis. Moreover, this work demonstrates the author's great insight and academic brilliance in the fields of finance, technological innovations and marketing vis-a-vis the market economy. From both theoretical and practical standpoint, this work is indeed a great achievement. Yeon Cheon Oh, President of Seoul National University

The beginning of the age of artificial intelligence and machine learning has created new challenges and opportunities for data analysts, statisticians, mathematicians, econometricians, computer scientists and many others. At the root of these techniques are algorithms and methods for clustering and classifying different types of large datasets, including time series data. Time Series Clustering and Classification includes relevant developments on observation-based, feature-based and model-based traditional and fuzzy clustering methods, feature-based and model-based classification methods, and machine learning methods. It presents a broad and self-contained overview of techniques for both researchers and students. Features Provides an overview of the methods and applications of pattern recognition of time series Covers a wide range of techniques, including unsupervised and supervised approaches Includes a range of real examples from medicine, finance, environmental science, and more R and MATLAB code, and relevant data sets are available on a supplementary website

The aim of the proposed volume will be to present new developments in the methodology and practice of CGE techniques as they apply to recent issues in international trade policy. The volume will be of interest to academic researchers working in trade policy analysis and applied general equilibrium, advanced graduate students in international economics, applied researchers in multilateral organizations, and policymakers who need to work with and interpret the results of CGE analysis.